Trajectories of pain recovery during the first 8 weeks after shoulder arthroplasty : results from the shoulder diary study using latent growth curve modeling
(2025) In Journal of Shoulder and Elbow Surgery- Abstract
Background: Perioperative stress or discomfort in shoulder arthroplasty (SA) patients can be reduced using more individually tailored patient education and expectation management. Most published studies assess pain and function for the first time at 6 weeks or 3 months. Consequently, there is no thorough understanding of day-to-day recovery trajectories within the first postoperative weeks, hindering effective patient education and expectation management in the early postoperative phase. In this study, we explored the distinct pain recovery trajectories that emerge for SA patients during their first 8 postoperative weeks and examined how patients in the identified subgroups differ in terms of sociodemographic and psychological factors.... (More)
Background: Perioperative stress or discomfort in shoulder arthroplasty (SA) patients can be reduced using more individually tailored patient education and expectation management. Most published studies assess pain and function for the first time at 6 weeks or 3 months. Consequently, there is no thorough understanding of day-to-day recovery trajectories within the first postoperative weeks, hindering effective patient education and expectation management in the early postoperative phase. In this study, we explored the distinct pain recovery trajectories that emerge for SA patients during their first 8 postoperative weeks and examined how patients in the identified subgroups differ in terms of sociodemographic and psychological factors. Methods: In our prospective multicenter cohort study, we included 230 SA patients who completed an 8-week postoperative diary containing daily Numeric Rating Scale of pain scores and medication use, weekly function scores, and twice-weekly quality of life scores. In addition, patients completed preoperative questionnaires regarding pain, function, and demographic and psychological factors. We used Latent Growth Curve Modeling to classify groups of patients based on their early pain recovery trajectories; models included smooth functions based on natural cubic splines to represent the different trajectories of pain scores over time in the latent classes. Results: Our final model contained 6 different classes whose trajectories differed during the first 2 weeks. The model contained random intercepts (ie, allowed for between-person variability around the initial pain score) and fixed slopes (ie, did not allow for between-person variability in subsequent change in pain scores over time) within each class. After the first 2 weeks, classes 1 through 4 (83.7%) were similarly stable with very low pain scores (the ‘Faster group’). Classes 5 and 6 (16.3%) had a slower decline in pain scores (the ‘Slower group’), but comparable scores to the Faster group at week 8. The Slower group also more frequently had American Society of Anesthesiologists score ≥3, was less often employed and had lower baseline Oxford Shoulder Score and EQ-5D visual analog scale scores. Both groups had similar recovery rates in Oxford Shoulder Score and EQ-5D visual analog scale scores, although the Slower group had lower scores than the Faster group. Conclusion: In this study, we distinguished 6 early recovery trajectories after total shoulder arthroplasty. Our results enable clinicians to reassure their patients before surgery, as 5 of 6 patients likely have very low pain scores (Numeric Rating Scale ≤2) after only 2 weeks. Also, the sixth patient is at almost similar low pain scores at 8 weeks postsurgery.
(Less)
- author
- Hesseling, Brechtje ; Snoeker, Barbara A.M. LU ; ten Brinke, Bart ; Slot, Karin ; Zwitser, Eline W. ; van Rosmalen, Joost ; Eygendaal, Denise and Mathijssen, Nina M.C.
- organization
- publishing date
- 2025
- type
- Contribution to journal
- publication status
- epub
- subject
- keywords
- growth mixture modeling, latent class growth analysis, latent growth curve modeling, Level I, longitudinal pain recovery trajectories, Prognosis Study, Prospective Cohort Design, short-term pain recovery, Shoulder arthroplasty
- in
- Journal of Shoulder and Elbow Surgery
- publisher
- Elsevier
- external identifiers
-
- pmid:40769237
- scopus:105015389660
- ISSN
- 1058-2746
- DOI
- 10.1016/j.jse.2025.06.016
- language
- English
- LU publication?
- yes
- id
- 20591cd5-c037-43ae-865f-491b28049b77
- date added to LUP
- 2025-11-13 15:39:31
- date last changed
- 2025-11-14 14:47:24
@article{20591cd5-c037-43ae-865f-491b28049b77,
abstract = {{<p>Background: Perioperative stress or discomfort in shoulder arthroplasty (SA) patients can be reduced using more individually tailored patient education and expectation management. Most published studies assess pain and function for the first time at 6 weeks or 3 months. Consequently, there is no thorough understanding of day-to-day recovery trajectories within the first postoperative weeks, hindering effective patient education and expectation management in the early postoperative phase. In this study, we explored the distinct pain recovery trajectories that emerge for SA patients during their first 8 postoperative weeks and examined how patients in the identified subgroups differ in terms of sociodemographic and psychological factors. Methods: In our prospective multicenter cohort study, we included 230 SA patients who completed an 8-week postoperative diary containing daily Numeric Rating Scale of pain scores and medication use, weekly function scores, and twice-weekly quality of life scores. In addition, patients completed preoperative questionnaires regarding pain, function, and demographic and psychological factors. We used Latent Growth Curve Modeling to classify groups of patients based on their early pain recovery trajectories; models included smooth functions based on natural cubic splines to represent the different trajectories of pain scores over time in the latent classes. Results: Our final model contained 6 different classes whose trajectories differed during the first 2 weeks. The model contained random intercepts (ie, allowed for between-person variability around the initial pain score) and fixed slopes (ie, did not allow for between-person variability in subsequent change in pain scores over time) within each class. After the first 2 weeks, classes 1 through 4 (83.7%) were similarly stable with very low pain scores (the ‘Faster group’). Classes 5 and 6 (16.3%) had a slower decline in pain scores (the ‘Slower group’), but comparable scores to the Faster group at week 8. The Slower group also more frequently had American Society of Anesthesiologists score ≥3, was less often employed and had lower baseline Oxford Shoulder Score and EQ-5D visual analog scale scores. Both groups had similar recovery rates in Oxford Shoulder Score and EQ-5D visual analog scale scores, although the Slower group had lower scores than the Faster group. Conclusion: In this study, we distinguished 6 early recovery trajectories after total shoulder arthroplasty. Our results enable clinicians to reassure their patients before surgery, as 5 of 6 patients likely have very low pain scores (Numeric Rating Scale ≤2) after only 2 weeks. Also, the sixth patient is at almost similar low pain scores at 8 weeks postsurgery.</p>}},
author = {{Hesseling, Brechtje and Snoeker, Barbara A.M. and ten Brinke, Bart and Slot, Karin and Zwitser, Eline W. and van Rosmalen, Joost and Eygendaal, Denise and Mathijssen, Nina M.C.}},
issn = {{1058-2746}},
keywords = {{growth mixture modeling; latent class growth analysis; latent growth curve modeling; Level I; longitudinal pain recovery trajectories; Prognosis Study; Prospective Cohort Design; short-term pain recovery; Shoulder arthroplasty}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Journal of Shoulder and Elbow Surgery}},
title = {{Trajectories of pain recovery during the first 8 weeks after shoulder arthroplasty : results from the shoulder diary study using latent growth curve modeling}},
url = {{http://dx.doi.org/10.1016/j.jse.2025.06.016}},
doi = {{10.1016/j.jse.2025.06.016}},
year = {{2025}},
}